4.7 Article

Stochastic dynamic analysis of nonlinear MDOF systems under combined Gaussian and Poisson noise excitation based on DPIM

期刊

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2022.109163

关键词

Random vibration; Nonlinear MDOF system; Combined Gaussian and Poisson white noise; excitation; Probability density integral equation; Direct probability integral method

资金

  1. National Natural Science Foundation of China [12032008, 11772079, 12102080]

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This paper proposes a novel direct probability integral method (DPIM) for analyzing the stochastic responses and dynamic reliability of nonlinear multi-degree-of-freedom (MDOF) systems under combined Gaussian and Poisson white noise excitation. The DPIM method is used to obtain the probability density function of the stochastic response by solving the deterministic motion equation and the probability density integral equation (PDIE) of the MDOF system. The effectiveness of the proposed method is demonstrated through the analysis of two nonlinear MDOF systems. The results show that considering the randomness of vehicle load and seismic excitation simultaneously in bridge design benefits the safe operation of the bridge.
Random vibration analysis of structures subjected to combined Gaussian and Poisson white noise excitation is a challenging issue. In this paper, a novel direct probability integral method (DPIM) is suggested to address stochastic responses and dynamic reliability of nonlinear multi-degree-offreedom (MDOF) systems under combined excitation. Firstly, probability density integral equation (PDIE) of MDOF system under combined excitation is derived based on the principle of probability conservation. Then, DPIM is proposed to achieve the probability density function of stochastic response by solving deterministic motion equation of MDOF system and PDIE in sequence. To solve PDIE, two techniques, i.e., partition of input probability space and smoothing of Dirac delta function, are introduced. From the perspective of probability conservation, furthermore, the equivalent relationship between the PDIE and the corresponding probability density differential equation of a Markov system under combined Gaussian and Poisson noise is established. Since Dirac delta function is analytically integrated as Heaviside function, the firstpassage dynamic reliability of MDOF system under combined excitation is readily evaluated by introducing the extreme value mapping of stochastic response. Finally, two nonlinear MDOF systems, including multiple-span bridge under combined vehicle load and non-stationary seismic excitation, are solved. Results demonstrate that the proposed DPIM is effective for random vibration and dynamic reliability analyses of MDOF structures excited by combined Gaussian and Poisson noise, and considering the randomness of vehicle load and seismic excitation simultaneously in the bridge design benefits the safe operation of bridge.

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